Dataset Information

EGFR-Binding Peptides: From Computational Design towards Tumor-Targeting of Adeno-Associated Virus Capsids.

ABSTRACT: The epidermal growth factor receptor (EGFR) plays a central role in the progression of many solid tumors. We used this validated target to analyze the de novo design of EGFR-binding peptides and their application for the delivery of complex payloads via rational design of a viral vector. Peptides were computationally designed to interact with the EGFR dimerization interface. Two new peptides and a reference (EDA peptide) were chemically synthesized, and their binding ability characterized. Presentation of these peptides in each of the 60 capsid proteins of recombinant adeno-associated viruses (rAAV) via a genetic based loop insertion enabled targeting of EGFR overexpressing tumor cell lines. Furthermore, tissue distribution and tumor xenograft specificity were analyzed with systemic injection in chicken egg chorioallantoic membrane (CAM) assays. Complex correlations between the targeting of the synthetic peptides and the viral vectors to cells and in ovo were observed. Overall, these data demonstrate the potential of computational design in combination with rational capsid modification for viral vector targeting opening new avenues for viral vector delivery and specifically suicide gene therapy.

SUBMITTER: Feiner RC

PROVIDER: S-EPMC7765298 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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EGFR-Binding Peptides: From Computational Design towards Tumor-Targeting of Adeno-Associated Virus Capsids.

Feiner Rebecca C RC Kemker Isabell I Krutzke Lea L Allmendinger Ellen E Mandell Daniel J DJ Sewald Norbert N Kochanek Stefan S Müller Kristian M KM

International journal of molecular sciences 20201215 24

The epidermal growth factor receptor (EGFR) plays a central role in the progression of many solid tumors. We used this validated target to analyze the de novo design of EGFR-binding peptides and their application for the delivery of complex payloads via rational design of a viral vector. Peptides were computationally designed to interact with the EGFR dimerization interface. Two new peptides and a reference (EDA peptide) were chemically synthesized, and their binding ability characterized. Prese ...[more]

PMID: 33333826

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Project description:BACKGROUND: Most methods available to predict protein epitopes are sequence based. There is a need for methods using 3D information for prediction of discontinuous epitopes and derived immunogenic peptides. RESULTS: PEPOP uses the 3D coordinates of a protein both to predict clusters of surface accessible segments that might correspond to epitopes and to design peptides to be used to raise antibodies that target the cognate antigen at specific sites. To verify the ability of PEPOP to identify epitopes, 13 crystallographically defined epitopes were compared with PEPOP clusters: specificity ranged from 0.75 to 1.00, sensitivity from 0.33 to 1.00, and the positive predictive value from 0.19 to 0.89. Comparison of these results with those obtained with two other prediction algorithms showed comparable specificity and slightly better sensitivity and PPV. To prove the capacity of PEPOP to predict immunogenic peptides that induce protein cross-reactive antibodies, several peptides were designed from the 3D structure of model antigens (IA-2, TPO, and IL8) and chemically synthesized. The reactivity of the resulting anti-peptides antibodies with the cognate antigens was measured. In 80% of the cases (four out of five peptides), the flanking protein sequence process (sequence-based) of PEPOP successfully proposed peptides that elicited antibodies cross-reacting with the parent proteins. Polyclonal antibodies raised against peptides designed from amino acids which are spatially close in the protein, but separated in the sequence, could also be obtained, although they were much less reactive. The capacity of PEPOP to design immunogenic peptides that induce antibodies suitable for a sandwich capture assay was also demonstrated. CONCLUSION: PEPOP has the potential to guide experimentalists that want to localize an epitope or design immunogenic peptides for raising antibodies which target proteins at specific sites. More successful predictions of immunogenic peptides were obtained when a peptide was continuous as compared with peptides corresponding to discontinuous epitopes. PEPOP is available for use at http://diagtools.sysdiag.cnrs.fr/PEPOP/.

Dataset Information

EGFR-Binding Peptides: From Computational Design towards Tumor-Targeting of Adeno-Associated Virus Capsids.

Publications

EGFR-Binding Peptides: From Computational Design towards Tumor-Targeting of Adeno-Associated Virus Capsids.

Similar Datasets

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